Means and Method For Improved Glycemic Control For Diabetic Patients

ABSTRACT

A glycemic control system includes a physician processor, remote processor, and a portable telephone having a data input mechanism, a display, and an internal processor for bi-directional communication with the physician&#39;s processor and the remote processor. A patient inputs data to the internal processor responsive to input from the physician&#39;s processor and then transmits the information to the remote processor where an optimized number of units to be administered is sent back and displayed on the portable telephone.

CROSS REFERENCE TO RELATED APPLICATIONS

This U.S. patent application is a continuation of, and claims priorityunder 35 U.S.C. §120 from, U.S. patent application Ser. No. 15/283,838,filed on Oct. 3, 2016, which is a continuation of U.S. patentapplication Ser. No. 14/861,427, filed on Sep. 22, 2015, which is acontinuation of U.S. patent application Ser. No. 13/617,776, filed onSep. 14, 2012, which is a continuation-in-part of U.S. patentapplication Ser. No. 13/610,287, filed on Sep. 11, 2012. The disclosuresof these prior applications are considered part of the disclosure ofthis application and are hereby incorporated by reference in theirentireties.

TECHNICAL FIELD

This disclosure is in the field of methods and devices to improve bloodglucose control for diabetic patients.

BACKGROUND

A background. the last several years, improved control of blood glucosefor patients in the hospital using the G+ algorithm created by Aseko,Inc. for patients on intravenous insulin injection has been shown tosignificantly improve glycemic control. Improved glycemic control isachieved when the patient does not experience hypoglycemia (too low ablood glucose) or hyperglycemia (too high a blood glucose). Bloodglucose levels below 70 mg/dl are considered to be a condition ofhypoglycemia and fasting blood glucose levels above 140 mg/dl areconsidered to be a condition of hyperglycemia. The G+ algorithm is usedby hospitals to prevent both hypoglycemia and hyperglycemia. This isaccomplished in the following way: first, the nurse would measure thepatient's blood glucose and place that value and the patient's name at acomputer station where the nurse is situated; second other pertinentinformation about the patient (for example, hemoglobin A1C, height,weight, the number of grams of carbohydrates at a recently eaten meal ora meal about to be eaten, etc.) would be provided from that nurse'sstation computer; third, the hospital's central computer would calculatethe dose of insulin to be delivered to that particular patient tomaintain normal blood glucose; and fourth, the nurse would administerthat number of units of insulin to that patient. Experience over severalyears has shown that this method has achieved excellent results inreducing the rates of hypoglycemia and hyperglycemia experienced bypatients being treated in a hospital.

More recently, GlyTec, LLC. (a subsidiary of Aseko, Inc.) has created analgorithm for improved glycemic control for those patients onsubcutaneously injected insulin. By the use of this algorithm, patientshaving subcutaneously administered insulin either within the hospital oroutside the hospital can improve their glycemic control. It would behighly advantageous for patients away from the hospital to experiencethe improved glycemic control that has been demonstrated using the G+algorithm at those hospitals where that system is available.

There have recently been several different apps on smart phones that canprovide information for the diabetic patient. For example, an app is nowavailable that provides a listing of the specific numbers ofcarbohydrates for different foods that can be eaten by the diabeticpatient to better judge how many units of insulin that are needed toimprove that patient's glycemic control after ingesting that number ofgrams of carbohydrates. However, there is no app currently availablethat shows a complete listing of foods from which a diabetic patientcould select an abbreviated list of those particular foods that thatpatient would have in his or her normal diet. Still further, no appexists that has in its memory the number of grams of carbohydrates forthose specific foods that that specific patient would select. Stillfurther, there is no remote computer system that can communicate with apatient's smart phone which remote computer would have in its memory thenumber of grams of carbohydrates for an extensive selection of foodsfrom which a specific patient could select a subset of such foods. Stillfurther there is no app that indicates the quantity of a specific foodthat the patient has eaten or is about to eat. Still further, there isno app available on any smart phone that could make contact with aremote computer system to indicate other conditions experienced by adiabetic patient that affect that patient's need for insulin. Forexample, there is no existing app that indicates if the patient isundergoing exercise or the severity of such exercise, no app to indicatehaving significant emotional distress, no app that states if the patientis having a menstrual period, or is about to go to sleep or has justwoken up from sleeping, or having a fever of a specific temperature, orany other condition that could affect a specific patient's need forinsulin. There is also no remote computer system that can keep a recordof the past experiences of a specific patient as to that patient's needfor insulin depending on a significant number of factors such as thosedescribed above and for that computer to suggest to that patient, basedon past experience, the optimum dose of insulin to be subcutaneouslyinjected when that information is requested by a specific app in thatpatient's smart phone. There is also no smart phone that has beenprogrammed to have the same capability as a remote computer system torecord all past patient inputs so as to inform the patient as to theoptimum number of units of insulin to inject based upon that patient'spast history. Other apps do exist that can keep record of blood glucoselevels and insulin usage and share this information with a patient'shealth care team, including IBGStar Diabetes Manager, which is used inconjunction with a specific blood glucose meter. However, this app doesnot calculate for the patient the optimum insulin dosage based on thatpatient's current body chemistry and personal history of insulin usageunder similar circumstance, and does not give the patient freedom to usewhichever glucose meter he or she prefers.

SUMMARY

One aspect of the disclosure provides a method of determining an insulindosage value to be administered to a subject including the steps of: (a)providing a remote processor for receiving and storing a first set ofsubject blood glucose parameters; (b) establishing a time periodselected from the group of pre-meal, post meal, mid-sleep, bedtime, ormiscellaneous; (c) determining a meal type selected from the group ofbreakfast, lunch, dinner, or snack; (d) obtaining a blood glucosereading of the subject at a selected one of the time periods and themeal types; and (e) providing a system processor coupled to the remoteprocessor. The system processor is configured to calculate a bloodglucose correction dosage dependent on a second set of subject bloodglucose parameters, and to adjust the blood glucose correction dosagewhen the selected time period and the meal type is pre-meal andbreakfast respectively as a function of the first and second sets of thesubject blood glucose parameters.

Implementations of the disclosure may include one or more of thefollowing features. In some implementations, the first set of subjectblood glucose parameters includes a mid-point of a target blood glucoserange, a hypoglycemia threshold value, an insulin sensitivity factor,and previous basal and insulin dosage values administered at previousselected time periods and meal types, and meal plan data for thesubject. Additionally, the second set of subject blood glucoseparameters may include the blood glucose reading of the subject, ahypoglycemia threshold, a mid-point target range of the subject and asubject insulin sensitivity value. In some examples, calculating theblood glucose correction dosage includes the steps of: (a) determiningif the blood glucose reading is greater than the hypoglycemia threshold;(b) determining if the blood glucose reading is greater than themid-point of the target blood glucose range; and (c) calculating acorrection dose as a function of the blood glucose reading, themid-point of the target blood glucose range and the subject insulinsensitivity value when the blood glucose reading is greater than thehypoglycemia threshold and the mid-point of the mid-point of the targetblood glucose range. In some examples, calculating a correction dosageincludes applying a formula and transmitting the correction dosage to asubject data display and the remote processor when the time period isselected from the group of post-meal, mid-sleep, bedtime ormiscellaneous. Calculating the correction dosage when the time period ispre-meal and the meal type is breakfast is followed by the steps of: (a)calculating a basal dosage; and (b) calculating an adjustment to theblood glucose correction dosage as a function of an adjustment factor,the meal plan data and a previous breakfast insulin dosage value. Insome examples, the step of calculating the basal dosage includes thesteps of: (a) determining whether a previous mid-sleep subject bloodglucose reading is available; and (b) determining whether the previousmid-sleep subject blood glucose reading is less than a previousbreakfast blood glucose reading; and (c) calculating the basal dosage asa function of an adjustment factor dependent upon the previous mid-sleepsubject blood glucose reading and a previous basal dose when theprevious mid-sleep subject blood glucose reading is less than theprevious breakfast subject blood glucose reading, and an adjustmentfactor dependent on the adjustment factor dependent on a previousbreakfast subject blood glucose reading and a previous basal dose whenthe subject blood glucose reading is greater than the previous subjectblood glucose reading; and (d) transmitting the basal dosage to thesubject data display and the remote processor.

In some implementations, calculating the correction dosage is followedby the step of calculating an insulin dosage value when the time periodis pre-med as a function of: (1) an adjustment factor, and a previousselected meal type insulin dosage value when the subject is on a mealplan wherein a predetermined number of carbohydrates is prescribed foreach of the meal types; and (2) the adjustment factor, an estimatednumber of carbohydrates to be ingested at a selected meal type and acalculated carbohydrate to insulin ratio when the subject is not on ameal plan.

In some examples, the step of determining a physical parameter of thesubject includes the step of determining if the subject is exercising.When the subject is exercising the method further includes determiningwhether the blood glucose reading is less than a midpoint of a targetblood glucose range of the subject. In some examples, the method furtherincludes instructing the subject to ingest a predetermined amount ofcarbohydrates for each predetermined time interval of exercise.

Another aspect of the disclosure provides an insulin dosage system foroptimizing insulin dosages to be administered to a subject. The insulindosage system includes a glucometer for reading the subject's bloodglucose value at a time period selected from the group of pre-meal, postmeal, mid-sleep, bedtime, or miscellaneous, for a meal type selectedfrom the group of breakfast, lunch, dinner, or snack. The insulin dosagesystem also includes a remote processor for recovering and storing afirst set of subject blood glucose parameters, and a system processorhaving a display coupled to the remote processor. The system processoris configured to calculate a blood glucose correction dosage dependenton a second set of subject blood glucose parameters, and adjust theblood glucose correction dosage when the selected time period, and themeal type are pre-meal and breakfast respectively as a function of thefirst and second sets of the subject blood glucose parameters. In someexamples, the first set of subject blood glucose parameters includes amid-point of a target blood glucose range, a hypoglycemia thresholdvalue, an insulin sensitivity factor, previous basal and insulin dosagevalues administered at previous selected time periods and meal types,and meal plan data for the subject. The second set of subject bloodglucose parameters may include the blood glucose reading of the subject,a hypoglycemia threshold, a mid-point target range of the subject and asubject insulin sensitivity value. In some examples, the systemprocessor may further be configured to: determine if the blood glucosereading is greater than the hypoglycemia threshold; determine if theblood glucose reading is greater than the mid-point of the target bloodglucose range; and calculate a correction dose as a function of theblood glucose reading, the mid-point of the target blood glucose rangeand the subject insulin sensitivity value when the blood glucose readingis greater than the hypoglycemia threshold and the mid-point of themid-point of the target blood glucose range. In some examples, theinsulin dosage system includes a transmitting mechanism for transmittingthe correction dosage to a subject data display and the remote processorwhen the time period is selected from the group of post-meal, mid-sleep,bedtime or miscellaneous. Where the time period is pre-meal and the mealtype is breakfast the system processor may be further configured tocalculate a basal dosage, and calculate an adjustment to the bloodglucose correction dosage as a function of an adjustment factor, themeal plan data and a previous breakfast insulin dosage value. Whencalculating the basal dosage, the system processor may be furtherconfigured to determine whether a previous mid-sleep subject bloodglucose reading is available and determine whether the previousmid-sleep subject blood glucose reading is less than a previousbreakfast flood glucose reading. Also when calculating the basal dosage,the system processor may be further configured to calculate the basaldosage as a function of an adjustment factor dependent upon the previousmid-sleep subject blood glucose reading and a previous basal dose whenthe previous mid-sleep subject blood glucose reading is less than theprevious breakfast subject blood glucose reading, and an adjustmentfactor dependent on the adjustment factor dependent on a previousbreakfast subject blood glucose reading and a previous basal dose whenthe subject blood glucose reading is greater than the previous subjectblood glucose reading. Finally, when calculating the basal dosage, thesystem processor may be further configured to transmit the basal dosageto the subject data display and the remote processor. The systemprocessor may be further configured to calculate an insulin dosage valuewhen the time period is pre-med as a function of an adjustment factor,and a previous selected meal type insulin dosage value when the subjectis on a meal plan wherein a predetermined number of carbohydrates isprescribed for each of the meal types, and the adjustment factor, anestimated number of carbohydrates to be ingested at a selected meal typeand a calculated carbohydrate to insulin ratio when the subject is noton a meal plan. In some examples, the system processor is furtherconfigured to calculate a recommended dosage of carbohydrates if thesubject is in the process of exercising has exercised within apredetermined time interval of the blood glucose reading. When thesubject is exercising, the system processor is further configured todetermine whether the blood glucose reading is less than a midpoint of atarget blood glucose range of the subject. In some examples, the systemprocessor is further configured to instruct the subject to ingest apredetermined amount of carbohydrates for each predetermined timeinterval of exercise.

The present disclosure is a means and also a method to improve glycemiccontrol for the diabetic patient who is out of the hospital and is oninsulin that is subcutaneously administered, via insulin pumps ormultiple daily injections. This disclosure requires a special app for atypical smart phone (such as the IPHONE® or the DROID® phone) that isdesigned to communicate data relative to glycemic control from thepatient's smart phone to a remote computer system and back to thepatient's smart phone. For the purposes of this specification, this appshall be called the “GlytApp.” An important advantage of the presentdisclosure is to improve the glycemic control for the diabetic patientwho is not in a hospital and who plans to be using insulin that is givensubcutaneously, and who can utilize the GlytApp that has been programmedinto his or her smart phone.

The basic concept of the present disclosure is that the patient'sphysician uses his/her computer and the Internet to first obtain aPatient ID# from the company that provides the GlytApp for a specificPatient ID#. This is accomplished by the physician (or any authorizedindividual who has the right to write a prescription) using the Internetto contact (for example) GlytApp.com. On the computer screen would thenappear: “Please enter the patient's name and a Patient ID# will beprovided.” When the operator would then place the patient's name, aPatient ID# would appear. For example, for a patient name William E.Jones, his Patient ID#, WJ-000-012 could then appear. This ID# wouldindicate that this is the twelfth patient enrolled whose initials are WJwho would have this ID #. After the first meeting the doctor when writesthe patient's name into his computer, a specific Patient ID# will appearon that computer screen. There is a great advantage in using twoinitials plus six numbers. This combination provides 676 million uniquePatient ID# s. In the very unlikely event that there is a duplication,the computer that is controlling the Patient ID# s would alarm thedoctor to use different initials for that patient. Another noveladvantage of the combination of the patient's initials with a serialnumber is that if the person typing in the Patient ID# at some futuretime has the wrong number for a specific patient of that specificdoctor, then the computer would inform the person who is typing that thePatient ID# as written is incorrect. By first obtaining a Patient ID#without providing any medical information about that patient, thepatient's privacy is readily protected. When only that Patient ID# isused instead of using the patient's name in future communications overthe Internet, that patient's privacy is also maintained.

Once the doctor (or nurse or medical assistant) has obtained the PatientID# for a patient while that patient is still in the doctor's office,the doctor would write a prescription for that patient over the Internetto the company that is providing the GlytApp. The patient at that timewill also be given a paper copy of the doctor's prescription and, at thepatient's request, that prescription could also be sent to the patient'ssmart phone or to his/her computer.

The physician would write into that patient's smart phone a prescriptioncovering many factors designed to prevent and to treat bothhyperglycemia and hypoglycemia. The patient's app (the GlytApp) wouldhave that prescription written into it typically by communicating withthe doctor's computer through the GlytApp remote computer system whichis used by that doctor for writing prescriptions for insulin usage forhis diabetic patients. Inputs into the prescription section of theGlytApp will include blood glucose target range, insulin type, and basaldose, and other necessary information. The GlytApp could also allow thepatient to select from a long list of foods those specific foods that aspecific patient would choose to eat. The remote computer system thatcan receive communications from that patient's GlytApp would be capableof converting those foods selected for a specific meal by the patient asto the number of grams of carbohydrates in that quantity of the foodsselected for that specific meal. The GlytApp would select (for example)whether the meal involved either a small, medium or large portion of aspecific food. As with food items that come in pieces, such as slices ofbread, the GlytApp could also send to a remote computer system thenumber of such pieces of such food. The remote computer system would beable to calculate for that patient the number of grams of carbohydratesdepending on the type and quantity of food ingested or to be eaten inthe near future by the patient. It is also conceived that the smartphone itself could add up all the grams of carbohydrates for the type offood and portion size selected by the patient and send the total numberof grams of carbohydrates to the remote computer system. If the patientinjects a certain number of units of insulin based upon a meal he/she isabout to eat, and if the patient then dose not eat that meal, then theGlytApp will provide the information that the patient needs relative toingesting sugar pills (or equivalent source of glucose) to preventhypoglycemia.

The algorithm used by the remote computer system to determine the numberof units of insulin that the patient should inject will be based uponseveral factors that include: the type and quantity of food ingested bythe patient, the time since that last food ingestion, if a meal is aboutto be eaten, if the patient is about to exercise, etc. One of the mostimportant capabilities of the remote computer system will be to knowpast history for each patient and to select a recommended number ofunits of insulin to be delivered based upon that patient's past history.This very important information is all contained for a specific patientin the memory of the remote computer system. For example, if undersomewhat similar conditions, the computer's recommendation led to toohigh a level of blood glucose, then a subsequent computer recommendationwould suggest a somewhat higher level of insulin units to be injected inorder to have a more normal blood glucose level. Conversely, if a priorrecommendation of units of insulin led to too low a level of bloodglucose, then in subsequent recommendations by the remote computersystem, a lower number of units of insulin to be injected would besuggested for those same conditions. The remote computer system wouldalso be programmed to adjust for many other factors that affect thepatient's blood glucose level such as exercise, having a menstrualperiod, about to go to sleep, having just awakened from sleep,undergoing emotional distress, sexual activity, or any other factor thatthe remote computer system will determine over a period of time thataffects that specific patient's need for insulin. This key ability toprovide the patient with essential health information by way of anaccurate calculation of insulin dosage sets this proposed GlytApp apartfrom the other apps for diabetics as described in the prior art.

For security purposes, for the remote computer system to send aninstruction to the patient's smart phone with an insulin recommendationit would be required that the computer know the serial number for thatGlytApp of that smart phone. When sending the notice of the number ofunits of insulin to be injected by the patient, the computer would sendto the smart phone some information that makes it known to the patientthat the remote computer system knows that it is communicating with thatspecific patient. For example, the remote computer system might send themessage which includes the patient's name or a specific password when itsends to the patient the number of units of insulin to be injected.

One implementation of the present disclosure starts with a physician whowill be able to write on his computer a prescription for a specificpatient who must have a smart phone in order to utilize the means andmethod of this disclosure. To keep this prescription confidential, itwould be delivered into the patient's smart phone at the doctor'soffice. Alternatively, the physician could send a new or revisedprescription by means of a secure link that identifies the patient bythat patient's unique serial number. The physician's prescription wouldinclude the type of insulin to be used by the patient, the right toreceive instructions from the remote computer system to inform thepatient as to the amount of insulin to deliver depending upon severalfactors including (but not limited to) the number grams of carbohydratesingested, how long in time since the last meal, how many minutes untilthe next meal, the number of grams of carbohydrates expected to beingested at the next meal, whether the patient is about to go to sleep,whether the patient has just awakened from having been asleep, whetherthe patient is having a menstrual period, the extent as to intensity andtime duration relative to the patient undergoing exercise, whether thepatient has a fever and stipulating the level of that fever, the extentof sexual activity, what the patient should do in the event of differentlevels of hypoglycemia or hyperglycemia as experienced by the patientfrom time to time, etc. The remote computer system that communicateswith the patient's smart phone would keep a record of all factors thataffect a specific patient's blood glucose and would learn from pastexperience how to suggest the appropriate number of units of insulin fora specific patient based upon the past experience of that specificpatient.

An additional important aspect of the present disclosure is that thepatient's physician would also write a prescription into that patient'ssmart phone as to what that patient should do in the event ofhypoglycemia or hyperglycemia. For example, the doctor's prescriptioncould include the recommendation to intake glucose according to certainfactors as calculated by the amount of ingested glucose necessary tocorrect hypoglycemia. This oral glucose to be ingested can be in theform of glucose gel, glucose tablets, orange juice, or other forms.Another prescription from the doctor could suggest that, for any levelof hypoglycemia, take the suggested number of sugar pills and thenmeasure the blood glucose 15 minutes later to make sure that thehypoglycemia was not becoming more severe. Also, for more extreme levelsof hypoglycemia or hyperglycemia, the doctor's prescription may alsoautomatically call the physician and a designated patient monitor todiscuss the situation with that patient.

If high levels of hyperglycemia persist, then the patient's monitor atthe company that has provided the GlytApp and/or the patient's doctorwould be informed of this condition. The doctor's prescription writteninto his computer and then transferred to the patient's smart phonecould include certain recommendations relative to hyperglycemia such asinject additional units of insulin if the blood glucose reading is toohigh, measure the blood glucose 15 to 30 minutes later and injectadditional insulin if the blood glucose level does not go into a normalrange, or cut back on foods with a high level of carbohydrates, orincrease exercise, or any other recommendation that would decrease thepatient's blood glucose.

The prior art in this area includes only apps capable of recordinginformation the patient inputs, and in some cases providing anuncomplicated method for sharing this information with the patient'sdoctor. The GlytApp not only incorporates those features, but,importantly, provides a two-way flow of information using an interactiveinterface whereby the information the patient provides is recorded,processed using a key algorithm, and informs the patient of the optimumdosage of insulin based on a variety of conditions. Because theappropriate insulin dosage for a particular patient at a particular timeis dependent upon many factors, many diabetic patients struggle withchoosing the exact right dosage for any given set of circumstances. Thissmartphone app is the only smartphone program that will help patientsaccomplish improved glycemic control.

Thus an advantage of one of the aspects of the disclosure is to improvea diabetic patient's glycemic control by the use of a special app (theGlytApp) on a patient's smart phone that has two-way communication witha remote computer system that has stored in its memory the past historyof that patient's need for insulin based upon a multiplicity of factorsthat affect that patient's blood glucose level.

Another advantage of the disclosure includes having a means to assurethe patient that the communication to that patient's smart phone fromthe remote computer system is in fact unique for that specific patient.

Still another advantage of the disclosure is to have the patient's smartphone receive a specific doctor directed recommendation as to what thatpatient should do in the event of experiencing either hyperglycemia orhypoglycemia.

Still another advantage of the disclosure is for the patient's smartphone to notify either or both that patient's physician and/or a patientmonitor if that patient experiences a potentially dangerous level ofhypoglycemia or hyperglycemia that has been programmed by that patient'sdoctor for that particular patient.

Still another advantage of the disclosure is for the patient's smartphone to request another blood glucose reading to be taken within ashort period of time after a prior reading if that first measured levelof blood glucose is potentially dangerous for that patient.

Still another advantage of the disclosure is for either the remotecomputer system or the patient's smart phone to provide for the patientthe range of units of insulin that have been suggested in the past bythe remote computer system for similar circumstances so that the patientcan be sure that the present suggestion for the number of units ofinsulin to be injected is within a reasonable range.

Still another important advantage of the disclosure is the unique methodthat the physician or the physician's assistant would use to have thepatient gain access to the GlytApp for that patient's smart phone andhaving a unique serial number for that patient while maintaining thecomplete privacy of all medical matters pertaining to that patient.

Still another advantage of the disclosure is that the smart phone itselfcould be used without a remote computer system to calculate the correctdose of insulin for a patient depending upon historical data of mattersthat affect the patient's blood glucose that have been stored in thememory of that smart phone.

Still another advantage of the disclosure is that, if the patient failscheck in at a specified time interval with his physician, an alert wouldbe sent to that patient indicating the potential need for medical carefor that patient.

Another aspect of the disclosure provides a system for improved glycemiccontrol for a diabetic patient. The system includes a smart phonecontrolled by the diabetic patient that includes a specialized appcalled a “GlytApp,” the smart phone having the capability to beprogrammed by a medical professional who is authorized to write aprescription into that patient's smart phone that enables that patientto access a remote computer system by means of the GlytApp, the GlytAppbeing designed to send to the remote computer system that patient'sreading of blood glucose as well as several other factors that affectthat patient's need for insulin including at least the type and quantityof food that the patient has ingested and also the time when that foodwas ingested or the time in the future when that food will be ingested.The remote computer system has the capability to calculate an optimizednumber of units of insulin to be injected by the patient at that timefor best controlling that patient's level of blood glucose. The numberof units of insulin to be injected is based upon the input parametersprovided by the patient's smart phone and also based upon the patient'spast history as stored in the memory of the remote computer system, asto the patient's past response to input parameters that affect thatpatient's need for insulin.

In some examples, the smart phone is also capable of displaying amessage from the remote computer system that assures the patient thatthe number of units suggested for subcutaneous injection by the patientis specifically directed for that specific patient by displaying thatpatient's name or displaying a password that is known to the patient. Insome examples, the smart phone displays a range of the units of insulinpreviously displayed by the smart phone under similar circumstances thatdetermined in the past the patient's need for injected insulin undersimilar circumstances.

The patient's smart phone may have the capability to transmit to theremote computer system several additional parameters that affect thatpatient's need for insulin. These parameters include, but are notlimited to, the any one of, several or all of the following parameters:if the patient has been exercising, the severity of any such exercising,if the patient is undergoing significant stress, if the patient isundergoing a menstrual period, if the patient is about to go to sleep,or if the patient is just arising from sleep, or if the patient has afever and the level of that fever.

The patient's smart phone may display an extensive list of foods and thepatient can place onto his or her smart phone a subset of the total listof displayed foods which that patient would normally eat and the smartphone also having a listing as to various quantities of such a subset offoods and the smart phone having the capability to transmit to theremote computer system the type of food eaten by the patient and therelative quantity of that food so that the remote computer system canestimate the quantity of carbohydrates in the food eaten by the patientand thereby provide a message to the patient's smart phone as to thenumber of units of insulin to be injected to best maintain a normallevel of blood glucose at that time for that patient. The quantity offood displayed on the patient's smart phone may be specified in threedifferent levels, namely small, medium, or large. Additionally oralternatively, the quantity of food displayed on the smart phone may belisted as to the number of such food items. Such food items include thenumber of slices of bread, the number of ears of corn, the number ofdrinks of an alcoholic beverage, the number of glasses of beer or anysimilar quantization of items of food eaten by the patient.

In some examples, the smart phone has the capability of displaying, tothe patient, what action to take if the patient's blood glucose showseither hypoglycemia or hyperglycemia. In some examples, the action to betaken is programmed into the patient's smart phone by that patient'sphysician. Additionally or alternatively, the action recommended by thesmart phone depends on a specific reading of hyperglycemia orhypoglycemia and/or the state of the patient being either mid-sleep orfasting blood glucose. In some examples, the occurrence of hypoglycemiacauses the smart phone to suggest to the patient, that the patient takespills or food that can increase the level of blood glucose for thatpatient at that time. The number of pills or the amount of foodsuggested to the patient being greater when there is a more extremelevel of hypoglycemia.

In some implementations, the occurrence of hyperglycemia causes thesmart phone to suggest to the patient to take an additional injection ofa specific number of units of insulin depending on the level ofhyperglycemia.

The occurrence of hyperglycemia may cause the patient's smart phone torecommend taking an additional injection of insulin and measuring thatpatient's blood glucose again in a period of time between 10 and 60minutes after receiving that additional injection of insulin. In someexamples, the smart phone contacts either or both the patient'sphysician or a patient monitor to inform that person as to a severeextent of either hypoglycemia or hyperglycemia that is being experiencedby the patient.

Yet another aspect of the disclosure provides a method to maintain theconfidentiality of medical information for a patient who is receivingthe GlytApp app. The method includes the following steps: (a) having adoctor decide that he wishes to give his patient a prescription toobtain the app (the GlytApp) for that patient's smart phone for optimumglycemic control; (b) having the doctor tell the patient that he wouldlike to prescribe the GlytApp if the patient has a smart phone and iswilling to pay a monthly fee to improve his/her glycemic control and thepatient agrees to that arrangement; (c) having the doctor then request aserial number for his patient from the company that operates the remotecomputer system that can communicate with that patient by means of theGlytApp; (d) providing the patient's name to the company by the doctorfollowed by the doctor receiving over the Internet an appropriate serialnumber that appears on the doctor's computer; and (e) having the doctorthen use that patient's serial number in all communications with thecompany in order to maintain the confidentiality of all medicalinformation pertaining to that patient.

Another aspect of the disclosure provides a system for improved glycemiccontrol for a diabetic patient. The system comprises a physicianprocessor, a remote processor, and a portable telephone. The remoteprocessor is in data communication and displaced from the physician'sprocessor for calculating an optimized number of units of insulin to beadministered at a specific time to the patient. The portable telephonehaving a data input mechanism and a display. The portable telephone hasan internal processor for bi-directional communication with thephysician's processor and the remote processor. The internal processoris configured to: (a) receive prescribed data from the physician'sprocessor; (b) receive patient input data taken at least from the groupof a glucometer reading at the specific time, type of food to beingested, type of food previously ingested; (c) transmit the patientinput data to the remote processor; and (d) receive from the remoteprocessor the optimized number of units to be administered. The remoteprocessor is configured to: (e) calculate as blood glucose correctiondosage dependent upon the patient input data to calculate the optimizednumber of units to be administered; and (f) transmit the optimizednumber of units to be administered to the physician's processor and theinternal processor. The remote processor and the internal processor maybe further configured to transmit and receive a unique set of patientspecific identifying data for display on the portable telephone display.In some examples, the internal processor is further configured todisplay a plurality of previously administered patient specific insulinunits based upon previously calculated correction dosages calculated bythe remote processor. In some examples, the patient input data includespatient physical condition data, the patient physical condition datataken from at least the group of whether or not the patient isexercising, the severity of the exercise, whether the patient isundergoing stress at the specific time, whether the patient isundergoing a menstrual period, whether the patient has a fever and thepatient's temperature.

In some examples, the internal processor is further configured to: (a)display a plurality of foods on the portable telephone display; (b)display a set of quantity amount of each of the foods previouslyingested or to be ingested by the patient; and (c) transmit to theremote processor the selected quantity amount and the selected foodswhich the patient has selected at the specific time. The remoteprocessor may be further configured to calculate the number ofcarbohydrates associated with the foods and the quantity amountsselected by the patient. The remote processor is further configured tocalculate the optimized number of units to be administered based uponthe select foods and the quantity amounts selected by the patient. Thequantity amount displayed on the portable telephone display is specifiedas small, medium, or large. In some examples, the prescribed dataincludes a specific action to be taken dependent on whether thepatient's blood glucose level determines whether the patient hashypoglycemia or hyperglycemia.

These and other advantages of the disclosure will become obvious to aperson of ordinary skill in this art upon reading the detaileddescription of this disclosure including the associated drawings aspresented herein.

DESCRIPTION OF DRAWINGS

FIG. 1 is a broad flow block diagram of the computer system forprocessing and calculating insulin dosages to be administered to asubject responsive to a particular meal type and a predetermined timeperiod.

FIG. 2 is a logic block diagram providing a broad logic flow of thelogic associated with the computer system and modules dependent uponwhether the meal type is pre-meal, post-meal, bedtime, mid-sleep, ormiscellaneous.

FIG. 3 is an information flow block diagram associated with processing aphysical condition of the subject.

FIG. 4 is a flow block diagram associated with determining a correctiondosage to be administered to the subject dependent upon input dataprovided by the subject associated with the meal type and the timeperiod.

FIG. 5 is a logic flow diagram for calculation of the current bolusassociated with an adjustment factor.

FIG. 6 is a flow block diagram showing the processing for calculatingupdated basal dosages.

FIG. 7 is a flow block diagram showing the adjustment factorcalculations based upon current blood glucose levels.

FIG. 8 illustrates the prescription form that would be sent by thepatient's physician to the company that would then provide the GlytAppfor that patient.

FIG. 9 is a system diagram for a novel system to improve glycemiccontrol for diabetic patients by using a remote computer system incommunication with that patient's smart phone.

FIG. 10 is a system diagram for a novel system to improve glycemiccontrol for a diabetic patient by using that patient's smart phone thathas been programmed to make optimum suggestions as to the number ofunits of insulin to be delivered after the patient's level of bloodglucose and other factors have been placed as inputs into that patient'ssmart phone.

FIG. 11A shows the extended list of options that the patient may choosefrom to indicate conditions from his or her present situation that mayfactor into the dose of insulin needed.

FIG. 11B is an extension of FIG. 11A that can be reached by scrollingdown the smart phone screen.

FIG. 12A shows a subset of all the foods that the patient has placedinto his smart phone based upon what that specific patient wouldtypically eat as selected from an extensive list of foods and includingwhat the patient would deem to be either small, medium or large portionsof that food.

FIG. 12B is an extension of FIG. 12A that can be reached by scrollingdown the smart phone screen.

FIG. 13 shows the display of the smart phone that would be received froma remote computer system that indicates the number of units and the typeof insulin to be injected into that patient based upon a measured levelof blood glucose that the patient placed into that smart phone.Additionally it indicates the expected range for the amount of insulinthat has been suggested on prior occasions for approximately the sameparameters including blood glucose reading and ingestion of food so thatthe patient can see if the number of units that is presently suggestedfor insulin injection is within that expected range.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

Referring now to FIG. 1, there is shown blood glucose in insulin dosageadministering system 100 for determining an insulin dosage value to beadministered to a subject. In particular, system 100 is directed tocalculating, processing and recommending blood glucose levels fordiabetic subjects at specific times prior to or subsequent to ingestionof food or other nutrients and calculating a recommended insulin dose tobe administered. System 100 is designed to provide the subject withcalculated insulin dosage instructions based upon nutritional andphysical information in combination with the personal history ofprevious insulin administration and resulting blood glucose levels.

The following definitions of the terminology used in the followingparagraphs are as follows:

Mid-point target blood glucose range (T_(m)) shall refer to themid-point of a target blood glucose range (or other blood glucose valuewithin the range) inserted into remote processor 114 by a physician orcaregiver for a subject. Although referring to “mid-point” of the bloodglucose range, the mid-point target data may be inserted as a functionof the mid-point of the mid-point target blood glucose range or someother input deemed appropriate by the subject's physician or caregiver.

Time periods shall refer to the time that a subject is taking a bloodglucose reading with a standard glucometer and further refers to apre-meal time period, a post-meal time period, a bedtime period, amid-sleep time period, or some miscellaneous time period when thesubject is taking the blood glucose reading.

Meal type shall refer to either breakfast, lunch, dinner, snack, ormiscellaneous associated with when the subject is taking the subject'sblood glucose reading.

Blood glucose reading shall be the blood glucose reading taken at apredetermined time period and associated with a meal type.

Bolus shall refer to recommended insulin dose administered for a mealtype and a time period.

Basal Dose shall refer to a total basal dosage of insulin to be takenfor one day.

Hypoglycemia threshold shall refer to a lower blood glucose value for aparticular subject provided by a physician or other caregiver.

Prior blood glucose doses and/or levels shall refer to previous bloodglucose doses and/or levels taken or calculated at previous time periodsassociated with a respective meal type.

Basal insulin type shall refer to the type or brand of long actinginsulin used with basal dose calculations.

Bolus insulin type shall refer to the type or brand of short actinginsulin used with meal bolus and correction doses of insulin.

Basal dose distribution shall refer to the frequency and distribution ofbasal doses for a particular day such as (1) once a day (SID); (2) twicea day (BID); or, (3) three times a day (TID).

Physical condition parameter shall refer to a physical condition of thesubject at the time that the blood glucose reading is being taken suchas whether or not the subject is exercising or plans to exercise.

Intermediate blood glucose correction dosage shall refer to a firstcalculation by processor 116 shown in FIG. 1.

Carbohydrate to insulin ratio is a subject specific factor based upon afunction of the total daily dose of insulin based upon the subject'sweight at the time of initialization of the system 100 processes.

Meal plan shall refer to whether or not the subject is limited toingesting a known number of carbohydrates for each meal type. When asubject is “on” a meal plan, the subject is generally prescribed apredetermined number of carbohydrates to be ingested at a selected mealtype.

Miscellaneous time period shall refer to blood glucose calculations at atime period which is not associated with the time periods of breakfast,lunch, dinner, or snack. Such a miscellaneous time period may beassociated with a subject fasting period when blood glucose calculationsare being processed.

Mid-sleep time period shall refer to blood glucose readings taken at atime during a time period when the subject is normally asleep, generallyat some point during a sleeping cycle of the subject.

Insulin sensitivity factor shall refer to a subject specific sensitivityto insulin, generally determined by a physician or care giver andinserted as a portion of the data stored in the remote processor.

System processor shall refer to an on-site processor which calculates auser's recommended insulin dosage value to be taken at a selected timeperiod and a selected meal type.

Remote processor shall refer to a processor which is coupled to thesystem processor and stores a first set of a subject's blood glucoseparameters and includes but is not limited to prior basal and bolusdosages, prior or previous blood glucose readings for selected mealtypes and time periods, subject specific hypoglycemia thresholds,prescribed mid-point of a subject's target range, a subject specificinsulin sensitivity factor, basal insulin type, bolus insulin type,basal dose distributions, and the number of carbohydrates a subject isrecommended to ingest for a selected meal type. The remote processor isgenerally locationally removed (but in communication) with the systemprocessor, however in some cases the remote processor may beincorporated with the system processor.

Referring now to FIG. 1, there is shown blood glucose system 100 forcalculating, processing, determining, and displaying a recommendedinsulin dosage value (bolus) to be administered to a subject. The broadblock diagram shown in FIG. 1 includes a glucometer reading (BG) whichis inserted by the subject in block 102. The subject takes his/her bloodglucose value with a standard glucometer well-known in the art andcommercially available. The glucometer generally provides the subject'scurrent blood glucose reading in mg/dl.

Further, data is inserted by the subject in block 101 as to the physicalcondition of the subject at the time of the taking of the blood glucosevalue. The data inserted in block 101 will further be describedthroughout the flow process and in particular with regard to FIG. 3. Ingeneral, data inserted into block 101 includes whether the subject iscurrently exercising or plans to exercise. Further, data is stored inremote processor 114 associated with prior basal dosages, prior bloodglucose doses administered for particular meal types and time periods(bolus), a subject specific hypoglycemia threshold determined by thephysician. Data to be included in block 105 is the estimated number ofcarbohydrates the subject will be ingesting at a particular meal type ifthe subject is not on a meal plan, as well as the number ofcarbohydrates recommended to be ingested for a particular meal type ifthe subject is on a prescribed meal plan. Further included in the datastored in remote processor 114 is the mid-point target blood glucoserange and the mid-point (T_(m)) inserted by a physician or othercaregiver for a particular subject.

The blood glucose reading taken in block 102 and the subject physicalcondition in block 101 is inserted into processor 116 on line 118.Within block 103, a determination of the physical condition of thesubject is made independent of further calculations within processor 116to be further detailed in relation to FIG. 3. Block 103 directsprocessor 116 to decision block 302 in FIG. 3 where the subjectindicates whether his condition is exercise. If the condition indecision block 302 is that the subject is not exercising and does notplan to exercise, the information flows on information line 320 back toblock 104 in FIG. 1 for further calculations to be further described infollowing paragraphs. From block 104, the information then flows todosing adjustment 108 detailed in FIG. 4 and then to subject display 110and to remote processor 114 for storing the data.

If the condition is an exercise condition, found in decision block 302of FIG. 3, the logic moves on line 326 to decision block 320 where it isdetermined whether the blood glucose level read in block 102 from theglucometer reading is less than or equal to the mid-point target bloodglucose range stored in remote processor 114. If the blood glucose levelis equal to or greater than the mid-point target blood glucose range,information is directed on line 322 to block 104 in FIG. 1 for furthercalculations and passes subsequently to display 110 and remote processor114.

If the blood glucose level value in decision block 320 is found to beless than the mid-point target blood glucose range, information isdirected on line 326 to block 318 where the subject is instructed to eata predetermined amount of carbohydrates for each predetermined minutesof exercise being planned or having been accomplished. This instructionis then provided to the patient on subject display 110 on line 324 andthe information is additionally sent to remote processor 114 for storageof the instructions.

Thus, whether the condition is exercise determined in decision block302, or whether or not the blood glucose level is less than themid-point of the target blood glucose range determined in decision block320, all logic then passes to blood glucose time period block 104 shownin FIG. 1 where the processing of block 104 is initiated in FIG. 2.

Once an intermediate processing or correction dosage calculation iscompleted in FIG. 2 for a particular meal type and time period, thelogic flows on line 120 (FIG. 1) to dosing adjustment block 108 which iscalculated in FIG. 4 to be further detailed and described. Once thedosing adjustment in block 108 has been made by processor 116,information flows on line 122 to subject data display 110 for providinga visual, audio or other type of sensory indication to the subject as tothe recommended insulin dosage to be administered. In overall concept,the information provided on line 122 to data display 110 is thentransported to remote processor 114 on line 124 for storage of all datacalculated. Remote processor 114 stores prior basal dosages, prioradministered blood glucose doses (bolus), hypoglycemia threshold, andmid-point target blood glucose range (T_(M)) which are transmitted toprocessor 116 on line 130 for processing.

Returning back to block 103, which has been detailed in the descriptionof FIG. 3, all information with regard to the physical condition of thesubject is additionally transported on line 126 to subject data display110 simultaneous with the information flowing on line 128 into block 104for determination of the blood glucose time period.

System processor 116 and subject data display 110 may be incorporatedwithin a standard Personal Computer System which has a standard monitorscreen for permitting the subject to visually obtain the recommendedinsulin dosage value being calculated within the system processor 116and/or the remote processor 114. The subject display monitor 110generally provides visual data to the user, however, as is known, audioinformation may also be transmitted to the subject.

Referring now to FIGS. 2 and 4-7, when the information flows into block104, the logic initially is directed to FIG. 2 where a decision is madeas to whether the time period at which the blood glucose level has beentaken is determined to be pre-meal, post-meal, bedtime, mid-sleep, ormiscellaneous.

Information flow from within block 104 of FIG. 1 is inserted on line 260to decision block 202 for determining whether the blood glucose readingtaken is pre-meal. If the blood glucose reading is taken prior tobreakfast, lunch, dinner, or snack, then information flows on line 262to decision block 204 to determine whether the meal type of the pre-mealtime period is breakfast.

If it is determined in decision block 204 that the pre-meal type isbreakfast, then the logic is transported on line 264 to block 212 forcalculation of a blood glucose correction dosage or intermediate bloodglucose correction dosage. Block 212 includes the processing of thelogic blocks in FIG. 4. The information in block 212 is inserted intodecision block 402 on line 424 for determination of whether insulin hasbeen administered within a predetermined time period which is generally2.0 hours, however, this is adjustable by a physician for a specificsubject. If insulin has been administered within a predetermined timeperiod, the logic then moves on line 426 to block 408 where “nocorrection dose” is recommended and the information returns to FIG. 2for further processing in block 220.

Where insulin has not been administered within a predetermined timeperiod found in decision block 402, information is directed to decisionblock 412 on line 430 for determination of whether the instant orcurrent blood glucose level reading from the glucometer in block 102 isless than the hypoglycemia threshold value stored in block 114. If theblood glucose reading is equal to or greater than the hypoglycemiathreshold value, information is transported on line 432 to decisionblock 404 where a determination is made whether the blood glucosereading is greater than the mid-point of the target blood glucose range(T_(M)).

If it is determined that the blood glucose reading is less than themid-point of the target blood glucose range, information is directed online 434 back to block 408 where there is “no correction doserecommended” and the information flows back to FIG. 2 for furtherprocessing on line 428 in block 220.

Where it is determined that the blood glucose reading is greater thanthe mid-point of the target blood glucose range in block 404, the logicthen passes on line 436 to calculation block 410 where the intermediatecorrection or correction insulin dosage is calculated. The intermediateblood glucose correction dosage calculated in block 410 is a function ofthe blood glucose reading, the mid-point of the blood glucose targetrange, and the subject sensitivity factor in accordance with theformula:

$\begin{matrix}{{CD} = \frac{\left( {{BG} - T_{m}} \right)}{\left( {1700\left( {\left( {T_{m} - 60} \right) \times S_{1} \times 24} \right)} \right)}} & (1)\end{matrix}$

-   -   Where: CD=correction dose calculated (units of insulin)    -   BG=blood glucose reading (mg/dl)    -   T_(m)=mid-point of blood glucose target range (mg/dl)    -   S₁=patient insulin sensitivity factor (units/mg/dl)

Once the blood glucose correction dosage is determined in calculationblock 410, information is directed to decision block 480 on line 438.Since the correction dosage and associated logic of FIG. 4 is used inconjunction with all time periods where the blood glucose value is takenincluding pre-meal, post-meal, bedtime, mid-sleep, and miscellaneous, aswell as meal types, breakfast, lunch, dinner, snack, bedtime andmid-sleep, the information on line 438 is inserted into the decisionblock 480 where it is once again determined whether the meal type andthe time period is breakfast and pre-meal.

If both of the conditions are met (e.g., meal type is pre-meal and timeperiod is breakfast), information then is directed on line 440 totransfer block 422 which is representative of FIG. 6. Referring now toFIG. 6, information from transitional block 422 passes on line 424 intodecision block 426 to determine whether a previous mid-sleep bloodglucose level has been determined and stored in either system processor116 and/or remote processor 114. If there is no previous mid-sleep bloodglucose level available or the subject does not take mid-sleep bloodglucose readings, information passes on line 428 to transfer block 642for further processing in FIG. 5.

If there is a previous mid-sleep blood glucose level availability,information is directed on line 430 to decision block 602 to determinewhether the previous mid-sleep blood glucose level was less than theprevious breakfast blood glucose level reading stored in remoteprocessor 114. If the previous mid-sleep blood glucose level is lessthan or equal to the previous breakfast blood glucose level, the logicpasses on line 614 to calculation block 604 for calculating anadjustment factor using the previous mid-sleep blood glucose level.

Calculation of the adjustment factor using the previous mid-sleep bloodglucose level is shown in FIG. 7 to be further detailed. Block 604calculations decision blocks are made in 702, 706, 710, and 714, as wellas calculation block 718 which provides for a particular adjustmentfactor associated with the blood glucose reading. The information isthen passed to block 608 in FIG. 6 for a Basal dose to be calculatedbased upon the adjustment factor.

If the previous mid-sleep blood glucose level is greater than theprevious breakfast blood glucose level in decision block 602,information is transported on line 630 to processing block 606 where theadjustment factor is calculated using the previous breakfast bloodglucose level in accordance with the adjustment factor found in FIG. 7.Thus, in both processing block 604 and 606, an adjustment factor iscalculated in the logic flow associated with FIG. 7.

Calculation blocks 604 and 606 are calculated in FIG. 7 where theinformation flows on line 722 to initial decision block 702 to determinewhether the blood glucose level is greater than or equal to 181 mg/dl.If the blood glucose level is greater than 181 mg/dl, then an adjustmentfactor is set in block 704 as being 1.2. If the blood glucose level isnot greater than or equal to 181 mg/dl, then information flows on line724 to decision block 706 where it is determined whether the bloodglucose level is within the range of 141 mg/dl to 180 mg/dl. If theblood glucose level is within the range defined in decision block 706,the adjustment factor is set to be 1.1 in block 708. If the bloodglucose level is not within the range determined in decision block 706,information is transported on line 726 to decision block 710 where it isdetermined whether the blood glucose level is greater than or equal to101 mg/dl and less than or equal to 140 mg/dl. If the blood glucoselevel is within the range defined in block 710, the adjustment factor isset in block 712 as 1.0. If the blood glucose level does not fall withinthe range associated with decision block 710, information is directed online 728 to decision block 714 where it is determined whether the bloodglucose level is within the range of 71 mg/dl to 100 mg/dl. If the bloodglucose level is within the range defined in block 714, the adjustmentfactor is set in block 716 to be 0.8. If the blood glucose level is notwithin the range associated with the decision made in decision block714, the blood glucose level must be less than or equal to 70 mg/dl asshown in block 718 and in this case, the adjustment factor is set inblock 720 as 0.8. The adjustment factors set in blocks 704, 708, 712,716, and 720 are dimensionless.

Once the proper adjustment factor is defined in blocks 704, 708, 712,716, or 720 information flows on respective lines 722, 724, 726, 728, or730 to transfer block 732 where information returns to either blocks 604or 606 in FIG. 6.

As stated, the adjustment factor after being calculated in FIG. 7, theinformation returns to FIG. 6 and in particular to blocks 604 and 606.The information in block 604 and 606 respectively pass on lines 632 or634 to calculation block 608 where the new basal dose is calculated. Thenew basal dose calculated in block 608 is the previous basal dosemultiplied by the adjustment factor and this value is inserted intoblock 610 to recommend the basal dose at the configured time interval.Information then flows on line 636 to block 638 to insert therecommended basal dose to the subject data display 110 and storage inthe system processor 116 and/or remote processor 114, as well as beingreturned on line 640 for further calculations of either the breakfast,lunch, dinner, or snack bolus associated with the logic flow in FIG. 5.

Thus, as shown in FIG. 4, if it is determined that both conditions ofthe time period being pre-meal and the meal type is breakfast,information is passed on line 440 to transfer block 422 for calculationsin FIG. 6 and then the information is inserted into transfer block 488for processing in accordance with the logic described in FIG. 5.

Returning now to FIG. 4, where once the correction dosage has beencalculated in block 410, and the information passed to decision block480, if it is determined in block 480 that both conditions of the timeperiod being pre-meal and the meal type being breakfast are not met,logic flows on line 492 to decision block 490. Decision block 490determines whether the time period is pre-meal. If the time period ispre-meal the logic moves on line 496 to transfer block 488 forprocessing in FIG. 5. If the time period is not pre-meal then the logicflow is directed to block 110 in FIG. 1 and the correction dose isinserted in accordance with the calculations made in calculation block410.

Returning back to FIG. 4 and decision block 412, if it is determined indecision block 412 that the blood glucose level is less than thehypoglycemia threshold level, information flows on line 450 to decisionblock 414. In decision block 414, it is determined whether the subjecthas impaired consciousness, and if the subject does not have impairedconsciousness information flows on line 452 to block 420 where thesubject is instructed to be given a predetermined dosage of oral glucoseand data is then sent directly to data display block 110. If the subjecthas impaired consciousness found in decision block 414, informationflows on line 454 to decision block 416 where it is determined whetherthere is IV access. If there is IV access, information on line 456 isinserted into block 418 where instructions are provided to give aD50IV=(100−BG)×0.04 amount to the subject. If there is no IV access,glucogen is then recommended to be administered in block 422.Information from blocks 420, 422, and 418 are passed on lines 458, 460,and 462 for information input to data display 110 and subsequentlyinserted into remote processor 114 of FIG. 1.

Returning now to FIG. 2, once the basal dose has been adjusted in block220 as associated with the processing in FIGS. 6 and 7, for a timeperiod which is pre-meal and a meal type which is breakfast, informationis directed to block 228 for calculation of the recommended insulindosage at breakfast or breakfast bolus.

Similarly, if the time period is pre-meal and meal type is lunch,calculations of the intermediate blood glucose correction dosage forlunch is calculated in FIG. 4. If the time period is pre-meal and themeal type is dinner, calculation of the intermediate blood glucosecorrection dosage is made in block 216. Similarly, if it is determinedthat the time period is pre-meal and that the meal type is a snack indecision block 210, a calculation of the blood glucose correction dosagefor the snack is calculated in block 218.

In all processing and calculation blocks 212, 214, 216, and 218, thecalculations are provided in association with the previous logic flowdescription given for the logic blocks in FIG. 4.

Information from FIG. 2 processing blocks 228, 222, 224, and 226 arecalculated in accordance with the logic flow in FIG. 5. Calculation ofthe breakfast, lunch, dinner, or snack bolus is shown in FIG. 5 withinformation passing from blocks 228, 222, 224, and 226 on line 530 todecision block 502 where it is once again determined whether thepre-meal time period is breakfast. If the pre-meal time period isbreakfast, information passes to calculation block 510 on line 532 forcalculation of the adjustment factor as previously detailed in the logicflow provided for FIG. 7.

If the time period is pre-meal and the meal type is breakfast,calculation of the adjustment factor is made in block 510 in accordancewith FIG. 7 as previously discussed. Information then passes to decisionblock 562 where there is a determination of whether the subject is on afixed meal plan. If it is determined that the subject is on a fixed mealplan, such as substantially the same number of carbohydrates to beingested at each time period and meal type, information then passes online 564 to calculation block 518 which calculates the current bolus inaccordance with the equation:

CB=CB _(i) ×AF  (2)

-   -   Where:    -   CB=current bolus (units of insulin)    -   CB_(i)=previous bolus administered at the previous Meal type and        time period (units of insulin)    -   AF=adjustment factor (dimensionless)

The current bolus is then passed on line 554 to subject data display 110and eventually to remote processor 114 as provided in FIG. 1. If it isdetermined that the subject is not on a fixed meal plan in decisionblock 562, information is directed through line 566 to calculation block586 where a number of calculations are performed. Initially, the totalprescribed daily basal dose of insulin in units of insulin per day iscalculated (TDD) in accordance with the formula:

TDD=TDD _(M) ×W _(S)  (3)

-   -   Where:    -   TDD=total prescribed daily basal dose of insulin (units of        insulin)    -   W_(S)=weight of subject (Kg.)    -   TDD_(M)=subject's Total Daily Dose Multiplier (a weighting        factor having dimensions of (units per Kg/day). Typically 0.25        for pediatric subjects, 0.3 for subjects with renal        insufficiency, 0.5 for adult subjects, or another subject        specific number)

Once the total prescribed daily basal dose is calculated in equation(3), within block 586, the meal of bolus (CB) is calculated by firstcalculating the carbohydrate to insulin ratio (dimensionless) inaccordance with the formula:

CIR=450×TDD  (4)

Where: CIR=current carbohydrate to insulin ratio (dimensionless)

TDD=total prescribed basal dose of insulin (units of insulin)

Using the previous selected pre-meal CIR to calculate the instant CIRfor a particular meal type is made in accordance with the formula:

$\begin{matrix}{{CIR}_{B,L,D,S} = \frac{{CIR}_{P_{B,L,D,S}}}{AF}} & (5)\end{matrix}$

-   -   Where: CIR_(B,L,D,S)=instant carbohydrate to insulin ratio for a        selected meal type of breakfast, lunch, dinner, or snack    -   CIR_(B,L,D,S)=previous carbohydrate to insulin ratio for        previous selected meal type of breakfast, lunch, dinner or snack    -   AF=adjustment factor

Finally, the current bolus to be recommended is derived from theEquation:

$\begin{matrix}{{CB} = \frac{C_{EST}}{{CIR}_{B,{L.D},S}}} & (6)\end{matrix}$

-   -   Where:    -   C_(EST)=estimated number of carbohydrates to be ingested at the        pre-meal time period for the current meal type (mg.)    -   CIR_(B,L,D,S)=calculated carbohydrate to insulin ratio        calculated in Equation 5

Subsequent to the calculation of the current bolus in block 518 or block586, information passes on respective lines 554 and 555 to subject datadisplay 110 and then to remote processor 114.

If it is determined in decision block 502 that the meal is notbreakfast, information is directed on line 536 to decision block 504where a decision is made as to whether the meal is lunch. If thepre-meal is lunch, then information is passed on line 538 to calculationblock 512 for calculation of the adjustment factor in FIG. 7 aspreviously discussed. Once the adjustment factor has been determinedfrom the logic flow in FIG. 7, information then is transported on line540 to fixed meal plan decision block 568. Decision block 568, similarto decision block 562, determines whether the subject is on a fixed mealplan and if the subject is on a fixed meal plan, information passes online 570 to calculation block 520 where the current bolus is calculatedin accordance with Equation 2. Where the subject is not on a fixed mealplan as determined in decision block 568, information passes on line 572to calculation block 588 which calculates the lunch bolus in accordancewith Equations 3, 4, 5 and 6 as previously discussed. Subsequently,information passes either on line 556 or 557 to subject display data 110and remote processor 114.

If it is determined that the meal type is not lunch in decision block504, information is transported on line 542 to decision block 506 whereit is determined whether the meal type is dinner. If the meal type isdinner, information is inserted to calculation block 514 on line 544 forcalculation of the adjustment factor provided by the logic in FIG. 7.Once the adjustment factor in FIG. 7 has been calculated, informationpasses on line 546 to decision block 574 determining whether the subjectis on a fixed meal plan. The decision block 574 is similar to decisionblocks 562 and 568. If it is determined that the subject is on a fixedmeal plan, information is then sent to calculation block 522 on line 576for calculation of the current bolus (CB) in accordance with Equation 2.If the subject is not on a fixed meal plan as determined in decisionblock 574, the information enters calculation block 590 for calculationof the dinner meal bolus in accordance with Equations 3, 4, 5 and 6.Information is then sent from either calculation block 522 or block 590on respective lines 558 and 559 to subject data display 110 and then toremote processor 114.

If it is determined in decision block 506 that the meal is not dinner,information then flows on line 548 to decision block 508 where it isdetermined whether the meal type is a snack. If it determined indecision block 508 that the meal is a snack, information passes on line550 to calculation block 516 where the adjustment factor is calculatedin accordance with FIG. 7. Information then passes on line 552 todecision block 580 which determines whether the subject is on a fixedmeal plan. If the subject is on a fixed meal plan as determined indecision block 580, information passes on line 582 to calculation block524 where the current bolus is calculated based upon equation 2. If thesubject is not on a fixed meal plan, the logic flows through line 584 tocalculation block 592 where the current meal bolus is calculated inaccordance with Equations 3, 4, 5, and 6. Information from block 524 orblock 592 is then transported on either Line 560 or 562 to subject datadisplay system 110 and then to remote processor 114.

In this manner, when the blood glucometer reading is taken asrepresented by block 102, and the physical condition is input by thesubject as represented by block 101, when the time period of the bloodglucose reading is taken is pre-meal as is determined in decision block202, a breakfast, lunch, dinner, and snack bolus is calculated by system100.

If the meal type is not a snack, then the time period is miscellaneousand passes on line 598 to transfer block 599 where logic is transferredto line 288 in FIG. 2. Processing is then provided in calculation block258 in accordance with the logic flow in FIG. 4.

Returning to FIG. 2, assuming that the blood glucose time period hasbeen determined not to be a pre-meal time period in decision block 202,the information passes on line 280 to decision block 230 where decisionblock 230 determines whether the time period is a post-meal time. If thetime period is determined to be post-meal, information is transported online 282 to decision block 232 where a decision is determined whetherthis is a breakfast post-meal glucometer reading. If the inputs providedby the subject is to a time period which is post-meal and the meal typeis breakfast, information is then transmitted to calculation block 240in FIG. 2. In this instance, there is no adjustment of the basal dose aswas the case when the time period was pre-meal (previously described)and the meal type was breakfast.

Calculation block 240 directs the information to FIG. 4 where acorrection dose is calculated in calculation block 410. All logic blockshave been previously detailed, however, in overview, if insulin has notbeen given within a predetermined period of time, for example two hoursas indicated in decision block 402, and the blood glucose reading isequal to or greater than the hypoglycemia threshold value (H₁) asdetermined in decision block 412, the information is directed todecision block 404 and if the blood glucose reading is determined to begreater than the mid-point target blood glucose range reading, thecorrection dose is calculated in calculation block 410. Responsively,subsequent to the calculations provided in calculation block 240, theresults and calculation of the post-meal breakfast correction istransmitted on line 284 to subject display 110 and remote processor 114for storage of the data calculated.

Similarly, as has previously been described for the pre-meal typecalculations in decision blocks 206, 208, and 210, a decision is made asto the fact whether the post-meal blood glucose reading is takensubsequent to lunch in decision block 234, dinner in decision block 236,or a snack in decision block 238. If it is determined that the post-mealblood glucose reading is subsequent to lunch in decision block 234, theinformation then is inserted into calculation block 242 for calculationof the post-meal lunch correction as associated with the logic flowpreviously described for FIG. 4.

If the decision in decision block 234 is that the post-meal was notlunch, the information then is directed to decision block 236 fordetermination of whether the post-meal blood glucose reading was dinnerand if it is dinner, the logic flows to block 244 and correction dosageas well as the subject meal bolus is made in association with FIG. 4.

If the blood glucose post-meal reading is a snack determined in decisionblock 238, similarly as previously described, the information isdirected to calculation block 246 for calculation in the same manner aspreviously described for the post-meal breakfast, lunch and dinnerdecisions. Information from blocks 240, 242, 244, and 246 are thenprovided on line 284 to both subject display 110 and remote processor114 for storage of the data and display of the recommended correctionreading.

If it is determined in decision block 230 that the blood glucose timeperiod is neither a pre-meal nor a post-meal, the information isdirected on line 290 to decision block 248 where it is determinedwhether the blood glucose taken is at the time period of bedtime (priorto sleep).

With the blood glucose reading provided in block 101, the information isdirected to calculation block 254 for insert into the logic flow of FIG.4. The logic in FIG. 4 in overall view, passes into correction dosecalculation block 410. The bolus for bedtime is then provided on line286 (FIG. 2) to both subject display system 110 and remote processor 114as shown in FIG. 1.

Assuming that the blood glucose type is not found to be bedtime indecision block 248, information is then inserted on line 292 to decisionblock 250 where the blood glucose reading time period is taken as“mid-sleep”. If the blood glucose reading is taken as a mid-sleep typereading, information then is inserted into calculation block 256 wherethe calculation correction is transmitted to the logic previouslydetailed for FIG. 4 and then inserted on line 286 to subject displaysystem 110 and remote processor 114 as shown in FIG. 2.

In the event that the blood glucose reading provided in block 101 is nota mid-sleep reading as determined in decision block 250, the informationthen passes on line 294 to calculation block 252 where the meal type isdefined as miscellaneous since it is neither for a breakfast, lunch,dinner, or snack reading. The information in 252 is then directed tocalculation block 258 where the bolus is calculated in accordance withFIGS. 4, 5, and 7.

In the event that the blood glucose reading meets the time criteriaperiod of a pre-meal, but is not at breakfast, lunch, dinner, or snackas determined in decision blocks 204, 206, 208, and 210, then the mealtype must be “miscellaneous” and the information passes on line 288 intoblock 252 and 258 for calculation of the correction dosage. As seen inFIG. 2, if the blood glucose reading is post-meal, but is not forbreakfast as determined in decision block 232, lunch as determined indecision block 234, dinner as determined in decision block 236, or thesnack as determined in decision block 238, again, the information isdirected on line 288 to 252 since the reading must be a “miscellaneous”reading. In all cases subsequent to the bolus being determined in 254,256, and 258, information calculated is then inserted for display insystem display 110 and stored in remote processor 114 for further use.

In overall concept, there is provided in FIGS. 1-7 a system fordetermining the insulin dosage value to be administered to a subjectdependent on many interrelated parameters. Input to system 100 includesa glucometer reading taken by the subject at a time period defined bywhether the blood glucose reading is taken pre-meal, post-meal, bedtime,or at some miscellaneous time. Remote processor 114 maintains instorage, prior basal dosages, hypoglycemia thresholds, target ranges andmid-points of target ranges, and subject insulin sensitivity factor. Thesubject provides a manual input on line 118 as represented by block 105as to the particular time period, whether such is pre-meal, post-meal,bedtime, or at some miscellaneous time. Additionally, the meal type suchas breakfast, lunch, dinner, or snack is inserted as represented byblock 105 for insert into processor 116 for determination of theappropriate correction factors and bolus to be calculated.

System 100 provides the patient with calculated insulin dosageinstructions based on nutritional and physical information, as well aspersonal history of insulin administration and resulting blood glucoselevels as previously described. The calculated insulin dosageinstructions are output to the subject on subject data display 110 whichcan be the monitor of a PC or through some other type of audio orsensory indication to the subject. The resulting data is then insertedinto remote processor 114 for storage of the data where prior basaldosages, prior blood glucose doses, hypoglycemia thresholds, subjectinsulin sensitivity factor, whether a meal plan is in effect, andmid-point of target ranges are maintained in storage.

Once the user has manually input the current glucometer reading ofhis/her blood glucose level from block 102 along with the time periodand meal type as represented in block 105, the subject further includesinput as to a physical condition from block 101. All of this data isthen inserted into processor 116 where the physical condition isinitially calculated independent of the further processing to beaccomplished by processor 116. The physical condition may requireadministration of a predetermined amount of carbohydrates as calculatedin FIG. 3 for each time period of exercise which has been accomplishedor is being planned and such is inserted into subject data display 110.Prior basal dosages and prior BG doses of the subject for previous timeperiods of pre-meal, post-meal, bedtime, or miscellaneous as well asprior BG doses associated with specific time periods and meal types isstored in remote processor 114 along with the hypoglycemia threshold andthe mid-point of the target range (T_(m)). All of this is inserted intoprocessor 116 on line 124 for calculations in blocks 104 and 108.

System 100 then processes all data drawing on the preset conditions andsubject history for determining optimum dosage levels of the subject'scurrent condition where all calculated data is then displayed asrepresented by block 110 and the calculated data is then stored inremote processor 114.

FIG. 2 is representative of the calculation blocks 104 and 108 in afurther breakdown of the processor calculation procedures. The system100 processes patient input of dietary events in FIG. 2 where initiallythe subject indicates whether the current blood glucose level read fromglucometer reading 102 is a time period of a pre-meal (decision block202), post-meal (decision block 230), prior to bedtime (decision block248), or mid-sleep cycle (decision block 250). If the time period isneither pre-meal, post-meal, bedtime, or during the mid-sleep cycle,then the time period is miscellaneous as represented by input block 252.Thus, all time periods are then represented and appropriate calculationscan be processed. Each of the decision blocks 202, 204, 206, 208, 210 or203, 232, 234, 236, 238, or 248 and 250 define individual series ofdecision blocks. A positive indication for one decision block implies anegative indication for other decision blocks in each series. This typeof event oriented organization permits the subject to expeditiouslyenter important information.

If the time period is pre-meal as determined in decision block 202, thepatient elects or indicates whether the pre-meal reading is breakfast asshown in decision block 204. As previously described, if the pre-meal isnot breakfast, the election is made for lunch in decision block 206,dinner in block 208, or a snack in decision block 210. An algorithmwithin processor 116 calculates the dosage correction for the plannedmeal using the calculation algorithm as previously described in FIG. 4in association with sub-algorithms provided in FIGS. 5-7 and in overallblock diagram shown in blocks 212, 214, 216, and 218 of FIG. 2.

In the time period of pre-meal and breakfast, the basal dose is adjustedas indicated in block 220 in association with the logic flow shown inFIG. 6.

For all pre-meals such as breakfast, lunch, dinner, snack, ormiscellaneous, the pre-meal bolus or recommended insulin dosage iscalculated in associated blocks 228, 222, 224, and 226. If the meal typeis neither breakfast, lunch, dinner, or a snack, then it is defined as amiscellaneous time period and the calculations for the bolus are inputinto block 252 and the calculated correction is made in block 258 aspreviously detailed. All recommended optimum doses to be taken in any ofthe time periods is then displayed to the subject on display 110 and thedata inserted into remote processor 114 for further use for subsequentblood glucose readings at specific meal types and time periods.

Mealtime nutritional information may be input by the subject and apost-meal bolus correction is calculated for correcting unacceptableblood glucose levels within the logic of processor 116 as indicated byblock 108 in FIG. 1 in association with FIG. 5. logic.

In the event that the time period of the blood glucose reading ispost-meal and determined in decision block 230, once again the meal typeis determined from the decision blocks 232, 234, 236, or 238 forrespective calculation of the post-meal type correction in respectiveblocks 240, 242, 244, and 246. Each of the decision blocks 230, 232,234, 236, and 238 determine a series of decision blocks where a positiveindication for one decision block defines a negative indication forother decision blocks in this series.

As shown in FIG. 2, if the time period is bedtime as determined indecision block 248, a pre-sleep blood glucose correction dose iscalculated in calculation block 254 associated with calculationsperformed in the logic steps as provided in FIG. 4. In the event thatthe blood glucose reading is mid-sleep as determined in decision block250, where it has been determined in decision block 248 that the timeperiod is not bedtime, the logic blows into decision block 250 where itis determined whether the time period is mid-sleep and if the timeperiod is mid-sleep, calculations are made in block 256 in accordancewith the logic flow in FIG. 4. All information is then inserted on line286 for insert into subject display 110 and remote processor 114.

In the event that one of the meal types previously discussed are foundfor either the pre-meal, post-meal, mid-sleep or bedtime calculations,the meal type is defaulted to input block 252 where it is determinedthat the meal type is miscellaneous and then passes to calculation block258 for calculation in accordance with the calculations processed inFIG. 4. Once again, the information from block 258 is inserted onto line286 for display and storage of the data in respective blocks 110 and114. As previously discussed, if the information exiting decision blocks210 and 238 indicate that the meal type was neither breakfast, lunch,dinner, or a snack, the information is directed to input block 252 andthen inserted into block 258 for calculation in accordance with thelogic associated with FIG. 4.

FIG. 4 is a sub-system which takes information from FIG. 2 and isassociated with the calculation blocks 212, 214, 216, and 218 for thepre-meal blood glucose reading time period, as well as logic blocks 240,242, 244, and 246 for the post-meal time period and blocks 254, 256, and258 for the time periods of bedtime, mid-sleep or miscellaneous. Thecalculation blocks of FIG. 2 are read into decision block 402 fordetermination of whether insulin has been administered within apredetermined time interval of the taking of the blood glucose readingand if insulin has been given within this predetermined time, there isno correction dosage recommended by system 100 and the information isreturned to FIG. 2 for further processing.

If the insulin has not been given within the predetermined period oftime (which is generally two hours), it is determined in decision block412 whether the subject's blood glucose level is below a pre-sethypoglycemia risk level (H₁) (hypoglycemia threshold). If it is notbelow the H₁, information then is directed to decision block 404 whereit is determined whether the blood glucose reading is greater than themid-point of the target range and if it is not, information is then sentback to block 408 where no correction dose is recommended and the systemreturns to FIG. 2.

If the blood glucose reading is greater than the mid-point of the targetrange as determined in decision block 404, the information then isdirected to block 410 where a correction dosage is calculated aspreviously discussed in relation to the correction dosage equation. Thecorrection dosage is then inserted into decision block 480 where it isdetermined whether the time period is pre-meal and whether the meal typeis breakfast. If the data corresponds to both of these two criteria, theinformation is then inserted into FIG. 6 for calculation of therecommended basal dose based upon previous mid-sleep blood glucoselevels and adjustment factors in FIG. 7. The logic then flows on line486 to FIG. 5 as shown by transfer block 488. If the information doesnot correspond to both a breakfast and pre-meal time period in decisionblock 420, the information then goes directly to FIG. 5 for furthercalculations as previously discussed.

In overall concept, if the decision in decision block 412 determinesthat the blood glucose level is below H₁, the system requests input indecision block 414 regarding the consciousness of the subject. Ifconsciousness is not impaired, the data then flows to block 420 foradministration of a predetermined amount of oral glucose (generally 15grams). If the subject does have impaired consciousness, the physicianor caregiver is then instructed to either administer glucogen in block420 or if there is IV access, for intravenous insertion of an insulinbased upon a 50% saline solution and insulin in accordance with thepreviously defined equations.

Sub-system 500 shown in FIG. 5 illustrates the logic flow withinprocessor 116 associated with adjustment factors calculated insub-system 700 shown in FIG. 7 which are incorporated into the meal timebolus calculations in the respective calculation blocks 228, 222, 224,and 226 of FIG. 2. For respective meal types, calculation adjustmentfactors are calculated in the logic flow of FIG. 7 and then the currentbolus is calculated as a function of the previous meal type bolus timesthe adjustment factor for each of the meal types in respective blocks518, 520, 522, and 524 as well as a determination of whether the subjectis on a meal plan. Information is then sent to subject display 110 andremote processor 114 subsequent to the calculations made.

Sub-system 600 shown in FIG. 6 describes the system 100 processing forincorporating the patient's personal fasting glucose levels into theadjustment factor (FIG. 7) for an increased defective recommended basaldose. A determination is made if it is determined that this is abreakfast and pre-meal meal type and time period in FIG. 4, theinformation is sent to block 422 where it then is transmitted on line424 to the decision block 426 to determine whether a mid-sleep glucoselevel has been taken and in decision block 426 and if it has not, suchreturns to FIG. 2 for calculation of the breakfast bolus in calculationblock 228. If the mid-sleep glucose level has been taken, the adjustmentfactor it is determined whether the previous mid-sleep blood glucoselevel is less than the previous breakfast blood glucose level indecision block 602 and if it is then the adjustment factor is calculatedin block 604 from the adjustment factors in FIG. 7. If the previousmid-sleep blood glucose level is equal to or greater than the previousbreakfast blood glucose level, then the adjustment factor is calculatedfrom FIG. 7 in block 606 and in this case, the adjustment factor iscalculated using the previous breakfast blood glucose level. In eithercases, information flows from either block 604 or 606 into block 608 onrespective lines 632 and 634 for calculation of the new basal dosagebeing the previous basal dose multiplied by the adjustment factor. Onceagain, the recommended basal dose at a particular time period is thenprovided in data block 610 which is then again sent to the subjectdisplay 110 and remote processor 114 as well as back to insertion intothe system in FIG. 5.

For a diabetic patient to receive the benefits associated with the useof a special app placed into that patient's smart phone, which app iscalled the “GlytApp,” he or she would follow the method described belowstarting when that patient would visit the doctor's office. Whenever theword “physician” or “doctor” is used herein, it shall also include othermedical professionals who would work with a physician such as a nurse,physician's assistant, medical technician, etc.

Method to Maintain Confidentiality for a Patient Obtaining the GlytApp

1. The doctor decides that he wishes to give his patient a prescriptionto obtain the app (the GlytApp) for that patient's smart phone foroptimum glycemic control.

2. The doctor tells the patient that he would like to prescribe theGlytApp if the patient has a smart phone and is willing to pay a fee toimprove his/her glycemic control.

3. If the patient agrees to this arrangement, then the following actionstake place.

4. The doctor then requests a serial number for his patient from thecompany that operates the remote computer system that can communicatewith that patient by means of the GlytApp.

5. When the doctor provides the patient's name to the company, thedoctor receives over the Internet an appropriate serial number thatappears on the doctor's computer. For example, a patient named WilliamE. Jones could get the serial number WJ-000-012. The two letters wouldbe used for those patients who have the initials WJ. So this serialnumber would be for the 12^(th) patient with the initials WJ that isenrolled to receive the GlytApp.

6. The doctor and the remote computer system that communicates with thepatient then uses that patient's serial number in all communicationsbetween the doctor, the patient, the company and the remote computersystem in order to maintain the confidentiality of all medicalinformation pertaining to that patient.

Once the doctor has confirmed with the patient that he/she wants theGlytApp, and the doctor has used the novel method described above toobtain a unique serial number for that patient, then the doctor willfill out on his computer a prescription form as shown in FIG. 8. Afterit is filled out by the doctor, this form would be sent over theInternet to the company that is providing the GlytApp for that patient.The goal of the form shown as FIG. 8 is to provide advice for thepatient that will be displayed on the patient's smart phone and willalso be available to the company that will monitor that patient's bloodglucose level. This form would appear on the patient's smart phone ifand only if that patient was in a state of either hypoglycemia orhyperglycemia. FIG. 8 also constitutes the prescription that anauthorized medical professional would use to allow the company to workwith that patient.

An important purpose of the prescription form shown in FIG. 8 is that ittells the patient what to do if various levels of hypoglycemia orhyperglycemia occur. Although this form shows certain treatments thatare suggested for hypoglycemia and hyperglycemia, the doctor can retainthe prerogative to make unique suggestions as to the information on thisform depending on what that doctor feels is an optimum response forhypo- or hyperglycemia depending on the needs of a specific patient.

FIG. 9 is a block diagram of a glycemic control system 10 of the presentdisclosure to optimize glycemic control for a diabetic patient 13. Afterthe patient 13 has agreed to obtain the GlytApp as described above, thephysician 11 uses his computer 12 and the method described above withthe assistance of FIG. 8 to set (with the assistance of the company) theGlytApp into the patient's smart phone 15. As shown in FIG. 8, this isaccomplished by the physician 11 sending a Prescription and BG Range tothe patient 13 which is the filled out form shown in FIG. 8. The filledout form shown in FIG. 8 is sent to the company by the physician 11 andthe company sets it into the smart phone 15 of the patient 13.

When the patient 13 provides a Blood Sample onto a paper strip that isread out by the blood glucose meter 14, that blood glucose meter 14 willindicate the patient's level of blood glucose. The patient 13 then callsup the GlytApp and uses it to place the value of that patient's bloodglucose into the smart phone 15. The patient 13 would then also put intohis/her smart phone 15 other pertinent data as requested by the GlytAppsuch as: 1) the type and quantity of food that the patient is about toeat; 2) the type and quantity of food that the patient has just eaten;3) the extent of any exercise that the patient is about to undergo; 4)whether or not the patient is having a menstrual period; 5) the extentto which the patient is having a specific level of stress; 5) the factthat the patient is about to go to sleep; 6) the fact that the patienthas just been awakened from sleep; 7) if the patient has a fever and ifso, the extent of that fever; 8) if the patient has had any recentchanges in circadian rhythm (jet lag); 9) any other factor that has beenshown to affect a particular patient's need for insulin. The collectionof these data and the measured level of blood glucose as shown in FIG.13 are then placed into the patient's smart phone 15 and they areindicated in FIG. 9 as the Algorithm Input Data that is sent to theremote computer system 16. Once any of these potentially pertinent dataentries have been placed into the GlytApp, these data are then sent by aspecific action of the patient 13 on his smart phone 15 to the remotecomputer system 16. These data constitute the Algorithm Input Data fromthe patient to the GlytApp and also into the remote computer system 16as shown in FIG. 9. Based on the patient's prior history that is storedin the memory of the remote computer system 16, for each unique patientserial number, the remote computer system then sends the CalculatedInsulin Dose (as seen in FIG. 9) to the patient's smart phone 15. Whenthat data is seen on the patient's smart phone 15, he/she injects anInsulin Dose as indicated in FIGS. 9 and 13. The remote computer system16 will have recorded essentially all the past glycemic history of eachpatient 13 so that the recommendation for an Insulin Dose is based uponthe past history for that particular patient 13. For example, if thepatient 13 at some past occasion had essentially the same conditions ofblood glucose, food to be eaten, exercise, etc. as is now sent to theremote computer system 16 and on that prior occasion the remote computersystem had sent a recommendation of 15 units of insulin to be deliveredand that resulted in too low a subsequent reading of blood glucose, thenat this time, the remote computer system would suggest an appropriatelylower dose of insulin (for example 13 units) to optimize that patient'sblood glucose. This system of having a computer adjust the insulin dosefor a specific patient 13 based upon his/her prior experience has beenshown in clinical trials to dramatically improve glycemic control ascompared to the patient 13 merely guessing as to how many units ofinsulin to deliver under different circumstances. Thus, the use of theGlytApp with the system shown in FIG. 9 will significantly improveglycemic control for those diabetic patients who would use the conceptsdescribed herein. It has been clearly shown that improved glycemiccontrol will decrease the possibility that the patient will suffer fromheart disease, loss of a limb, loss of eyesight or any of the otherproblems typically associated with uncontrolled diabetes.

An important aspect of the glycemic control system 10 shown in FIG. 9 isthat which occurs when the patient 13 is experiencing hypoglycemia orhyperglycemia. If either of those events occurs, then the remotecomputer system 16 will send an Out-of Range BG Alert to a companymonitor 17 as shown in FIG. 9. Also, all readings of the patient's bloodglucose indicated in FIG. 9 as the BG Reading can be sent to the companythat has provided the GlytApp for that patient 13. Such data could alsobe sent directly to the physician 11 or it could be sent to thephysician 11 through the company monitor 17. The physician 11 coulddirectly contact the patient 13, or it could be arranged that thecompany monitor 17 informs the patient 13 of the Out-of-Range BG Readingand that monitor could also provide (as seen in FIG. 9) someConversation-Instructions to guide that diabetic patient. The physician11 could select either to contact the patient 13 directly or have anyinstructions to the patient 13 be provided by the company monitor 17. Itis also understood that this system to “inform the patient's physician”could take place without any company monitor 17 being involved butrather would appear on the patient's smart phone.

By the use of the glycemic control system 10 shown in FIG. 9 it ispossible to dramatically improve the glycemic control for any and allpatients who would use a smart phone GlytApp as described herein.

FIG. 10 is a simplified system that uses a smart phone glycemic controlsystem 20 to better control a patient's blood glucose without the use ofa remote computer system. The glycemic control system 20 has thephysician 21 use his computer 22 to provide for the patient 23 aPrescription and BG Range limits in a manner similar to that describedfor FIG. 9. For the system 20, all the calculations are accomplishedwithin the smart phone 25 as operated by the patient 23. As with thesystem 10 of FIG. 9, the patient's blood glucose meter 24 is used toprovide a Blood Sample that the blood glucose meter 24 uses to measurethe blood glucose of the patient 23. When the patient 23 inputs all theAlgorithm Input Data (as described above for FIG. 9) into the smartphone 25, the smart phone 25 does all the computation similar to theremote computer system 16 of FIG. 9, to provide the Calculated InsulinDose as shown in FIG. 10. The patient 23 then injects the CalculatedInsulin Dose as also shown in FIG. 10. As with the system of FIG. 9, ifthere is an Out-of-Range BG Reading, that information is sent to thephysician 21 directly from the smart phone 25. The advantage of thesystem of FIG. 10 is that all the calculations are done within the smartphone 25 so that communication with a remote computer system is notneeded. This system would be particularly valuable for patients who liveor frequently travel to a region in the world where access to theInternet is limited or not available. The disadvantage of the system 20is that a large remote computer system has much better computing poweras compared to that which is typically available from a smart phone 25.It should be understood that the computer system in the smart phone 25would have to provide the recommendation as to how many unit of insulinto inject based upon a large variety of input data as was described forthe remote computer system 16 of FIG. 9.

FIG. 11A shows a list of options that the patient may choose from toindicate conditions about his or her present situation that may factorinto the dose of insulin needed. These conditions include but are notlimited to whether the patient is going to sleep or has just awakened,the current stress level of the patient, whether the patient has a feverand if so the severity of that fever, whether or not the patient isexperiencing jet-lag, whether the patient is about to exercise and if sothe severity of that exercise, whether the patient has just eaten or isabout to eat, and any other special factors that pertain to thepatient's current condition and the severity of those factors. Otherfactors not shown (such as having a menstrual period) may also belisted. If the patient does not give indication for any one of theoptions, it is taken to mean that that particular option is notcurrently a factor in the patient's condition. FIG. 11B is an extensionof FIG. 11A that can be reached by scrolling down the smart phonescreen.

FIG. 12A illustrates the type and quantity of foods that the patient hasselected from an extensive list of such foods that that patient wouldregularly eat. From that subset on that patient's smart phone, thepatient could communicate with a remote computer system or with his ownsmart phone to indicate the type and quantity of food that the patientis about to eat or has just eaten. The computer system in either theremote computer system 16 of FIG. 9 or the smart phone 25 of FIG. 10would have in its memory the number of grams of carbohydrate for each ofsuch foods. The quantity of food could be judged as to a small (S),medium (M) or large (L) portion as shown in FIGS. 12A and 12B. Also, anyfood that comes as pieces (such as slices of bread) could be indicatedas to a number of pieces such as the numbers 1, 2 and 3 as shown forslices of bread in FIGS. 12A and 12B.

The lower portion of FIG. 13 displays on the patient's smart phone theexpected range of insulin for that the patient based upon prioroccasions when there were similar input parameters into either theremote computer system or the patient's smart phone. If the dose assuggested in FIG. 13 does not come within range of what is shown in thelower portion of FIG. 13, then the patient might request a rerun fromthe remote computer system or from his smart phone to make sure that thenew reading is reasonable. FIG. 13 illustrates a typical LCD displaythat would be seen on the patient's smart phone that indicates to thepatient that he is identified by name (John Smith) and either smartphone 15 or 25 is telling the patient how much insulin to injectdepending on the input parameters that the patient put into the GlytApp.It is important that each patient knows that the information is personalfor that specific patient. By having the patient's name displayed withthe number of units of insulin to deliver, the patient immediately knowsthat this information is specifically for himself or herself.

Although this disclosure has been described in connection with specificforms and embodiments thereof, it will be appreciated that variousmodifications other than those discussed above may be resorted towithout departing from the spirit or scope of the disclosure as definedin the appended claims. For example, functionally equivalent elementsmay be substituted for those specifically shown and described, certainfeatures may be used independently of other features, and in certaincases, particular locations of elements, steps, or processes may bereversed or interposed, all without departing from the spirit or scopeof the disclosure as defined in the appended claims.

Various other modifications, adaptations and alternative designs are ofcourse possible in light of the teachings as presented herein. Thereforeit should be understood that, while still remaining within the scope andmeaning of the appended claims, this disclosure could be practiced in amanner other than that which is specifically described herein.

What is claimed is:
 1. A method comprising: receiving, at dataprocessing hardware, patient condition parameters during a pre-meal timefrom a user device controlled by a patient, the patient conditionparameters comprising a number of carbohydrates consumed by the patientand an exercise parameter for the patient, and the pre-meal timeassociated with a meal type corresponding to one of breakfast, lunch, ordinner, wherein the user device is configured to: receive, in a userinterface executing on the user device, inputs from the patient for eachpatient condition parameter during the pre-meal time; and transmit thepatient condition parameters from the user device to the data processinghardware; determining, by the data processing hardware, a recommendeddosage of insulin for the patient to administer based on the patientcondition parameters; storing, by the data processing hardware, therecommended dosage of insulin and the patient condition parameters inmemory hardware in communication with the data processing hardware; andtransmitting the recommended dosage of insulin from the data processinghardware to the user device, the recommended dosage of insulin, whenreceived by the user device, causing the user interface to display therecommended dosage of insulin.
 2. The method of claim 1, whereindetermining the recommended dosage of insulin for the patient toadminister comprises: determining a recommended meal bolus based on thenumber of carbohydrates consumed by the patient for the associated mealtype; obtaining previous patient condition parameters and a previousdosage of insulin administered by the patient for the associated mealtype from the memory hardware, the previous patient condition parameterscomprising a previous exercise parameter substantially equal to theexercise parameter associated with the patient condition parametersreceived during the pre-meal time; obtaining a previous next scheduledblood glucose measurement from the memory hardware, the previous nextscheduled blood glucose measurement resulting from the previous dosageof insulin administered by the patient; determining whether the previousnext scheduled blood glucose measurement is less than a hypoglycemiablood glucose limit for the patient; when the previous next scheduledblood glucose measurement is less than the hypoglycemia blood glucoselimit, determining a reduced insulin dosage value to prevent a nextscheduled blood glucose measurement from falling below the hypoglycemiablood glucose limit; and subtracting the reduced insulin dosage valuefrom the recommended meal bolus to determine the recommended dosage ofinsulin for the patient to administer.
 3. The method of claim 2, whereindetermining the recommended meal bolus comprises: obtaining acarbohydrate-to-insulin ratio for the patient from the memory hardware,the carbohydrate-to-insulin ratio input to the memory hardware by amedical professional computing device associated with an authorizedmedical professional; and dividing the number of carbohydrates consumedby the patient by the carbohydrate-to-insulin ratio to determine therecommended meal bolus.
 4. The method of claim 3, wherein thecarbohydrate-to-insulin ratio is calculated as follows:CIR=450×TDD wherein CIR is the carbohydrate-to-insulin ratio and TDD isa total prescribed daily dose of insulin for the patient based on aweight of the patient.
 5. The method of claim 1, wherein the exerciseparameter comprises a duration and/or severity of an exercise planned bythe patient or recently completed by the patient.
 6. The method of claim5, further comprising: determining, by the data processing hardware,carbohydrate intake instructions for the patient including apredetermined amount of carbohydrates for the patient to ingest based onthe duration and/or severity of the exercise; and transmitting thecarbohydrate intake instructions to the user device, the userinstructions when received by the user device, causing the userinterface executing on the user device to display the predeterminedamount of carbohydrates for the patient to ingest.
 7. The method ofclaim 1, further comprising: receiving, at the data processing hardware,a blood glucose measurement of the patient during the pre-meal time fromthe user device; obtaining, by the data processing hardware, an insulinsensitivity factor for the patient and a target blood glucose rangedefined by upper and lower blood glucose limits for the patient from thememory hardware, the insulin sensitivity factor and the target bloodglucose range inputted to the memory hardware by a medical professionalcomputing device associated with an authorized medical professional;determining, by the data processing hardware, whether the blood glucosemeasurement exceeds a midpoint of the target blood glucose range for thepatient; and when the blood glucose measurement exceeds the midpoint ofthe target blood glucose range for the patient: determining, by the dataprocessing hardware, a correction dose based on a function of the bloodglucose measurement, the mid-point of the target blood glucose range andthe insulin sensitivity factor; and transmitting the correction dosefrom the data processing hardware to the user device, the correctiondose, when received by the user device, causing the user interfaceexecuting on the user device to display the correction dose.
 8. Themethod of claim 7, wherein the correction dose is calculated as follows:${CD} = \frac{\left( {{BG} - T_{m}} \right)}{\left( {1700\left( {\left( {T_{m} - 60} \right) \times S_{1} \times 24} \right)} \right)}$wherein CD is the correction dose, BG is the blood glucose measurement,T_(m) is the mid-point of the target blood glucose range, and S₁ is theinsulin sensitivity factor.
 9. The method of claim 7, wherein the userdevice is configured to: receive the blood glucose measurement from ablood glucose meter in communication with the user device; and transmitthe blood glucose measurement of the patient to the data processinghardware.
 10. The method of claim 7, wherein the user device isconfigured to: receive, in the user interface, a blood glucose inputfrom the patient indicating the blood glucose measurement; and transmitthe blood glucose measurement of the patient to the data processinghardware.
 11. A system comprising: a user device controlled by a patientand having a screen, the user device configured to: display a userinterface on the screen; and receive, in the user interface displayed onthe screen, inputs from the patient for patient condition parametersduring a pre-meal time, the patient condition parameters comprising anumber of carbohydrates consumed by the patient and an exerciseparameter for the patient, and the pre-meal time associated with a mealtype corresponding to one of breakfast, lunch, or dinner; and dataprocessing hardware in communication with the user device, the dataprocessing hardware configured to perform operations comprising:receiving the patient condition parameters from the user device;determining a recommended dosage of insulin for the patient toadminister based on the patient condition parameters; storing therecommended dosage of insulin and the patient condition parameters inmemory hardware in communication with the data processing hardware; andtransmitting the recommended dosage of insulin from the data processinghardware to the user device, the recommended dosage of insulin, whenreceived by the user device, causing the user device to display therecommended dosage of insulin in the user interface.
 12. The system ofclaim 11, wherein determining the recommended dosage of insulin for thepatient to administer comprises: determining a recommended meal bolusbased on the number of carbohydrates consumed by the patient for theassociated meal type; obtaining previous patient condition parametersand a previous dosage of insulin administered by the patient for theassociated meal type from the memory hardware, the previous patientcondition parameters comprising a previous exercise parametersubstantially equal to the exercise parameter associated with thepatient condition parameters received during the pre-meal time;obtaining a previous next scheduled blood glucose measurement from thememory hardware, the previous next scheduled blood glucose measurementresulting from the previous dosage of insulin administered by thepatient; determining whether the previous next scheduled blood glucosemeasurement is less than a hypoglycemia blood glucose limit for thepatient; when the previous next scheduled blood glucose measurement isless than the hypoglycemia blood glucose limit, determining a reducedinsulin dosage value to prevent a next scheduled blood glucosemeasurement from falling below the hypoglycemia blood glucose limit; andsubtracting the reduced insulin dosage value from the recommended mealbolus to determine the recommended dosage of insulin for the patient toadminister.
 13. The system of claim 12, wherein determining therecommended meal bolus comprises: obtaining a carbohydrate-to-insulinratio for the patient from the memory hardware, thecarbohydrate-to-insulin ratio input to the memory hardware by a medicalprofessional computing device associated with an authorized medicalprofessional; and dividing the number of carbohydrates consumed by thepatient by the carbohydrate-to-insulin ratio to determine therecommended meal bolus.
 14. The system of claim 13, wherein thecarbohydrate-to-insulin ratio is calculated as follows:CIR=450×TDD wherein CIR is the carbohydrate-to-insulin ratio and TDD isa total prescribed daily dose of insulin for the patient based on aweight of the patient.
 15. The system of claim 11, wherein the exerciseparameter comprises a duration and/or severity of an exercise planned bythe patient or recently completed by the patient.
 16. The system ofclaim 15, wherein the operations further comprise: determiningcarbohydrate intake instructions for the patient including apredetermined amount of carbohydrates for the patient to ingest based onthe duration and/or severity of the exercise; and transmitting thecarbohydrate intake instructions to the user device, the userinstructions when received by the user device, causing the user deviceto display the predetermined amount of carbohydrates for the patient toingest in the user interface.
 17. The system of claim 11, wherein theoperations further comprise: receiving a blood glucose measurement ofthe patient during the pre-meal time from the user device; obtaining aninsulin sensitivity factor for the patient and a target blood glucoserange defined by upper and lower blood glucose limits for the patientfrom the memory hardware, the insulin sensitivity factor and the targetblood glucose range inputted to the memory hardware by a medicalprofessional computing device associated with an authorized medicalprofessional; determining whether the blood glucose measurement exceedsa midpoint of the target blood glucose range for the patient; and whenthe blood glucose measurement exceeds the midpoint of the target bloodglucose range for the patient: determining a correction dose based on afunction of the blood glucose measurement, the mid-point of the targetblood glucose range and the insulin sensitivity factor; and transmittingthe correction dose from the data processing hardware to the userdevice, the correction dose, when received by the user device, causingthe user to display the correction dose in the user interface.
 18. Thesystem of claim 17, wherein the correction dose is calculated asfollows:${CD} = \frac{\left( {{BG} - T_{m}} \right)}{\left( {1700\left( {\left( {T_{m} - 60} \right) \times S_{1} \times 24} \right)} \right)}$wherein CD is the correction dose, BG is the blood glucose measurement,T_(m) is the mid-point of the target blood glucose range, and S₁ is theinsulin sensitivity factor.
 19. The system of claim 17, furthercomprising a blood glucose meter in communication with the user deviceand configured to measure blood glucose measurements of the patient,wherein the user device is configured to: receive the blood glucosemeasurement from the blood glucose meter; and transmit the blood glucosemeasurement of the patient to the data processing hardware.
 20. Thesystem of claim 17, wherein the user device is configured to: receive,in the user interface, a blood glucose input from the patient indicatingthe blood glucose measurement; and transmit the blood glucosemeasurement of the patient to the data processing hardware.